Pinned Repositories
2-AXIS_BLDC_CAMERA_GIMBAL
A two axis camera gimbal stabillizer with the use of BLDC motors.
3-Axis-Camera-Gimbal-Stabilizer
A feedback control system for 3-axis camera gimbal stabilizer
500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
500 AI Machine learning Deep learning Computer vision NLP Projects with code
ADRC-Visualization
ADRC(Active Disturbance Rejection Control) vs PID Simulation
adrc_quadrotor
ADRC uses an Extended state observer to linearize the Quadrotor's Nonlinear dynamics (similar to Feedback linearization). This makes it capable of eliminating disturbances (robustness).
Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
Attitude-Control-Using-Chebyshev-Neural-Network
Re-Implementation of paper "Active attitude fault-tolerant tracking control of flexible spacecraft via the Chebyshev neural Network"
Attitude-Estimation-of-Quadcopter
Attitude estimation of Quadcopter using Kalman Filter, Extended Kalman Filter and Unscented Kalman Filter
Attiude-OrbitConUnderDisturbances
Attitude & Orbit Control for Spacecraft under disturbances.
SAR-attitude-control-using-RL
Synthetic Aperture Radar attitude control using Backstepping controller and Deep Reinforcement Learning
wangwanglianhe's Repositories
wangwanglianhe/2-AXIS_BLDC_CAMERA_GIMBAL
A two axis camera gimbal stabillizer with the use of BLDC motors.
wangwanglianhe/ADRC-Visualization
ADRC(Active Disturbance Rejection Control) vs PID Simulation
wangwanglianhe/adrc_quadrotor
ADRC uses an Extended state observer to linearize the Quadrotor's Nonlinear dynamics (similar to Feedback linearization). This makes it capable of eliminating disturbances (robustness).
wangwanglianhe/Attiude-OrbitConUnderDisturbances
Attitude & Orbit Control for Spacecraft under disturbances.
wangwanglianhe/Computer-Vision-Assisted-UAV-detection-and-tracking
This System track the Flaying object and Detect the object using various Machine learning algoritm like Support vector maching,KNN,Random forest and convoluted Neural network.
wangwanglianhe/CopterSim
A high-fidelity simulation model developed in Simulink that compatible with different types of multicopters.
wangwanglianhe/dcm-imu
The DCM-IMU algorithm is designed for fusing low-cost triaxial MEMS gyroscope and accelerometer measurements. An extended Kalman filter is used to estimate attitude in direction cosine matrix (DCM) formation and gyroscope biases online.
wangwanglianhe/directional-singularity-escape-avoidance-for-gyroscopes
This code accompanies the paper: Valk, L., Berry, A., and Vallery, H., "Directional Singularity Escape and Avoidance for Single-Gimbal Control Moment Gyroscopes," Journal of Guidance, Control, and Dynamics. DOI: 10.2514/1.G003132
wangwanglianhe/Disturbance_observer
In this note, disturbance rejection control (DRC) based on unknown input observation (UIO), and disturbance-observer based control (DOBC) methods are revisited for a class of MIMO systems with mismatch disturbance conditions. In both of these methods, the estimated disturbance is considered to be in the feedback channel. The disturbance term could represent either unknown mismatched signals penetrating the states, or unknown dynamics not captured in the modeling process, or physical parameter variations not accounted for in the mathematical model of the plant. Unlike the high-gain approaches and variable structure methods, a systematic synthesis of the state/disturbance observer-based controller is carried out. For this purpose, first, using a series of singular value decompositions, the linearized plant is transformed into disturbance-free and disturbance-dependent subsystems. Then, functional state reconstruction based on generalized detectability concept is proposed for the disturbance-free part. Then, a DRC based on quadratic stability theorem is employed to guarantee the performance of the closed-loop system. An important contribution offered in this article is the independence of the estimated disturbance from the control input which seem to be missing in the literature for disturbance decoupling problems. In the second method, DOBC is reconsidered with the aim of achieving a high level of robustness against modeling uncertainties and matched/mismatched disturbances, while at the same time retaining performance. Accordingly, unlike the first method, DRC, full information state observation is developed independent of the disturbance estimation. An advantage of such a combination is that disturbance estimation does not involve output derivatives. Finally, the case of systems with matched disturbances is presented as a corollary of the main results.
wangwanglianhe/drl_uav
Deep reinforcement learning for UAV in Gazebo simulation environment
wangwanglianhe/DynamicsF17-Gimbal
ENGR2340 : Dynamics FA2017 Final Project : 2-Axis Gimbal
wangwanglianhe/fqrouter
anti-GFW router
wangwanglianhe/gimbal-1
wangwanglianhe/gimbal_mtt_rectangle
Gimbal control to include multiple targets in the FOV of a camera
wangwanglianhe/gimbalcontrol
Model and Control three axis Gimbal using brushless motor with drone parameter input
wangwanglianhe/Hybrid_Fuzzy_Kalman_Filter
Mixed Kalman-Fuzzy Sliding Mode State Observer in Disturbance Rejection Control of a Vibrating Smart Structure Atta Oveisi*1, Tamara Nestorović1 1Ruhr-Universität Bochum, Mechanik adaptiver Systeme, Institut Computational Engineering, D-44801, Bochum, Germany. E-Mail: atta.oveisi@rub.de ABSTRACT In the controllers that are synthesized on a nominal model of the nonlinear plant, the parametric matched uncertainties and nonlinear/unmodeled dynamics of high order nature can significantly affect the performance of the closed-loop system. In this note, owing to the robust character of the sliding mode observer against modeling perturbations, measurement noise, and unknown disturbances and due to the non-fragile behavior of the Kalman filter against process noise, a mixed Kalman sliding mode state-observer is proposed and later enhanced by the addition of an intelligent fuzzy agent. In light of the proposed technique, the chattering phenomena and the conservative boundary neighboring layer of the high gain sliding mode observer are addressed. Then, a robust active disturbance rejection controller is developed by using static feedback of the estimated states using direct Lyapunov quadratic stability Theorem. The reduced order plant for control design purposes is subjected to some simulated square-integrable disturbances and is assumed to have mismatch uncertainties in system matrices. Finally, the robust performance of the closed-loop scheme with respect to the mentioned perturbation signals and modeling imperfections is tested by implementing the control system on a mechanical vibrating smart cantilever beam. Keywords: Fuzzy system; Nonlinear control; Active disturbance rejection; Kalman Filter; Vibration suppression.
wangwanglianhe/iot
Internet of Things 这是一个最小Internet of Things ，一个Internet of Things相关的毕业设计产生的一个简化的Internet of Things 。
wangwanglianhe/IOTs
wangwanglianhe/machinevision-toolbox-matlab
Machine Vision Toolbox for MATLAB
wangwanglianhe/Master-thesis-Gimbaled-thruster
Parametric study of lunar landers - Gimbaled thruster
wangwanglianhe/Matlab-ComputerVision
Car Tracking, Lane Detection, Traffic Sign Recognition, Homography, Color Segmentation, Visual Odometry
wangwanglianhe/openRobotics
Sharing the joy of robot programming in the spirit of open source
wangwanglianhe/PyUAVSim
Python simulator for small UAVs that can be used for designing and tuning autopilots
wangwanglianhe/qrsim2
Quadrotor / UAV Simulator using Matlab, Simulink and Flightgear Visualization
wangwanglianhe/self-balancing-robot-kit
The supplementary online material for the article: FUZZY CONTROL OF SELF‐BALANCING ROBOTS: A CONTROL LABORATORY PROJECT
wangwanglianhe/SMC-of-mechanical-arm-DOB
SMC of mechanical arm based on disturbance observer
wangwanglianhe/T2FSModellingUD
Uniform design based interval type-2 neuro-fuzzy system
wangwanglianhe/TalkUAV_Sim
一起写无人机仿真程序 https://zhuanlan.zhihu.com/talkuav
wangwanglianhe/UAV_obstacle_avoidance_controller
UAV Obstacle Avoidance using Deep Recurrent Reinforcement Learning with Temporal Attention